Description: This paper analyzes the U. S. Treasury monthly interest rates from 1953 to 1992, and the daily rates from 1981 to 1992 for various forms of chaotic behavior. The primary analysis was in determining the Burst Exponent by the use of Rescaled Range Analysis. This paper also discusses other possible uses of Fractional Brownian Motion in Finance Theory, Macroeconomics, and Actuarial Science. From Actuarial Research Clearing House 1994 VOL. 1.

Description: This paper discusses contracts sold by states which promised to provide tuition in the future for a fixed price. Because these contracts provide a benefit whose dollar value is uncertain at the time of sale, these contracts contain significant risks to the states and create a challenge to the actuaries who opine on the adequacy of the trust funds to provide the benefits promised by these contracts. This article discusses some of the implications of the method used by the major states to project tuition inflation and explores other possible methods. From Actuarial Research Clearing House 1993, VOL. 3.

Description: The primary focus of this 1997 presentation from the 32nd Actuarial Research Conference is the adaptation of the representative scenario method such that the distribution of the primary rates used for product pricing, are consistent, regardless of the initial random number seed. A preliminary question is how many stochastically generated scenarios are required for consistency. This presentation looks at the implications of: the use of antithetic random normal deviates upon the scenario process, ways of modifying the candidate list, and the choice function within the representative scenario process.

Description: This paper describes a theory of long-term interest-rate trends that was propounded in 1899 by an actuary, Charlton T. Lewis. The paper then presents a preliminary examination of how well that theory stands up in the light of 20th-century experience. The purpose is to invite more thorough evaluation by any experts who find the theory possibly useful.

Description: This 1997 presentation from the 32nd Actuarial Research Conference develops a stochastic generator for the generation of scenarios of the S&P 500 index, dividend yield, consumer price index, and U.S. Treasury yields. The authors first create a set of 'stylized facts' for these series. They estimate statistical models for these series. These in-sample statistical models are themselves not suitable for generation of scenarios for decision making, but instead are additional 'stylized facts' that assist in model development. The 'best' statistical model according to standard statistical model selection criteria can easily lead to a model that is highly unsuitable for generation of scenarios for decision making. The authors develop a stochastic generator that is suitable for decision making under uncertainty.